Prediction of antimicrobial peptides based on sequence alignment and support vector machine-pairwise algorithm utilizing LZ-complexity

BioMed Research International

Volumn 2015, Issue , 2015, Pages

  Ng, Xin Yi ^a   Rosdi, Bakhtiar Affendi ^b   Shahrudin, Shahriza ^a  

^a SCHOOL OF PHYSICS   (Malaysia)

^b SCHOOL OF CHEMICAL ENGINEERING   (Malaysia)

Author keywords

[No Author keywords available]

Indexed keywords

POLYPEPTIDE ANTIBIOTIC AGENT; ANTIINFECTIVE AGENT; PEPTIDE;

ALGORITHM; AMINO ACID SEQUENCE; ARTICLE; DATA ANALYSIS; INTERMETHOD COMPARISON; PREDICTION; SEQUENCE ALIGNMENT; SUPPORT VECTOR MACHINE; BIOLOGY; DRUG DESIGN; PROCEDURES; PROTEIN DATABASE; SENSITIVITY AND SPECIFICITY; SEQUENCE ANALYSIS;

BACTERIA (MICROORGANISMS);

ALGORITHMS; ANTI-INFECTIVE AGENTS; COMPUTATIONAL BIOLOGY; DATABASES, PROTEIN; DRUG DESIGN; PEPTIDES; SENSITIVITY AND SPECIFICITY; SEQUENCE ALIGNMENT; SEQUENCE ANALYSIS, PROTEIN; SUPPORT VECTOR MACHINE;

EID: 84924598117     PISSN: 23146133     EISSN: 23146141     Source Type: Journal    
DOI: 10.1155/2015/212715     Document Type: Article

References (64)

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32. G. Wang, X. Li, and Z. Wang, "APD2: The updated antimicrobial peptide database and its application in peptide design," Nucleic Acids Research, Vol. 37, supplement 1, pp. D933-D937, 2009.
33. S. Lata, B. K. Sharma, and G. P. S. Raghava, "Analysis and prediction of antibacterial peptides," BMC Bioinformatics, Vol. 8, article 263, 2007.
34. Y. Sang and F. Blecha, "Antimicrobial peptides and bacteriocins: alternatives to traditional antibiotics," Animal Health Research Reviews, Vol. 9, no. 2, pp. 227-235, 2008.
35. Z. Wang and G. Wang, "APD: the antimicrobial peptide database," Nucleic Acids Research, Vol. 32, pp. D590-D592, 2004.
36. P. Bulet, R. Stöcklin, and L. Menin, "Anti-microbial peptides: from invertebrates to vertebrates," Immunological Reviews, Vol. 198, pp. 169-184, 2004.
37. S. Thomas, S. Karnik, R. S. Barai, V. K. Jayaraman, and S. Idicula-Thomas, "CAMP: a useful resource for research on antimicrobial peptides," Nucleic Acids Research, Vol. 38, no. 1, Article ID gkp1021, pp. D774-D780, 2009.
38. S. Joseph, S. Karnik, P. Nilawe, V. K. Jayaraman, and S. Idicula-Thomas, "ClassAMP: a prediction tool for classification of antimicrobial peptides," IEEE/ACM Transactions on Computational Biology and Bioinformatics, Vol. 9, no. 5, pp. 1535-1538, 2012.
39. R. Hammami and I. Fliss, "Current trends in antimicrobial agent research: chemo- and bioinformatics approaches," Drug Discovery Today, Vol. 15, no. 13-14, pp. 540-546, 2010.
40. M. Torrent, M. V. Nogués, and E. Boix, "Discovering new in silico tools for antimicrobial peptide prediction," Current Drug Targets, Vol. 13, no. 9, pp. 1148-1157, 2012.
41. P. Wang, L. Hu, G. Liu et al., "Prediction of antimicrobial peptides based on sequence alignment and feature selection methods," PLoS ONE, Vol. 6, no. 4, Article ID e18476, 2011.
42. X. Xiao, P. Wang, W.-Z. Lin, J.-H. Jia, and K.-C. Chou, "IAMP-2L: a two-level multi-label classifier for identifying antimicrobial peptides and their functional types," Analytical Biochemistry, Vol. 436, no. 2, pp. 168-177, 2013.
43. Z. Hajisharifi, M. Piryaiee, M. M. Beigi, M. Behbahani, and H. Mohabatkar, "Predicting anticancer peptides with Chou's pseudo amino acid composition and investigating their mutagenicity via Ames test," Journal of Theoretical Biology, Vol. 341, pp. 34-40, 2014.
44. H. Peng, F. Long, and C. Ding, "Feature selection based on mutual information: criteria of max-dependency, max-relevance, and min-redundancy," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 27, no. 8, pp. 1226-1238, 2005.
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46. T. Huang, X.-H. Shi, P. Wang et al., "Analysis and prediction of the metabolic stability of proteins based on their sequential features, subcellular locations and interaction networks," PLoS ONE, Vol. 5, no. 6, Article ID e10972, 2010.
47. K.-C. Chou and H.-B. Shen, "Recent progress in protein sub-cellular location prediction," Analytical Biochemistry, Vol. 370, no. 1, pp. 1-16, 2007.
48. H.-B. Shen and K.-C. Chou, "PseAAC: a flexible web server for generating various kinds of protein pseudo amino acid composition," Analytical Biochemistry, Vol. 373, no. 2, pp. 386-388, 2008.
49. A. Lempel and J. Ziv, "On the complexity of finite sequences," IEEE Transactions on Information Theory, vol. IT-22, no. 1, pp. 75-81, 1976.
50. H. C. Muh, J. C. Tong, and M. T. Tammi, "AllerHunter: a SVM-pairwise system for assessment of allergenicity and allergic cross-reactivity in proteins," PLoS ONE, Vol. 4, no. 6, Article ID e5861, 2009.
51. L. Liao and W. S. Noble, "Combining pairwise sequence similarity and support vector machines for detecting remote protein evolutionary and structural relationships," Journal of Computational Biology, Vol. 10, no. 6, pp. 857-868, 2003.
52. F. H. Waghu, L. Gopi, R. S. Barai, P. Ramteke, B. Nizami, and S. Idicula-Thomas, "CAMP: collection of sequences and structures of antimicrobial peptides," Nucleic Acids Research, Vol. 42, no. 1, pp. D1154-D1158, 2014.
53. S. F. Altschul, W. Gish, W. Miller, E. W. Myers, and D. J. Lipman, "Basic local alignment search tool," Journal of Molecular Biology, Vol. 215, no. 3, pp. 403-410, 1990.
54. C.-C. Chang and C.-J. Lin, "LIBSVM: a library for support vector machines," ACM Transactions on Intelligent Systems and Thechnology, Vol. 2, no. 3, article 27, 2011.
55. K.-C. Chou and C.-T. Zhang, "Prediction of protein structural classes," Critical Reviews in Biochemistry and Molecular Biology, Vol. 30, no. 4, pp. 275-349, 1995.
56. K.-C. Chou and D. W. Elrod, "Protein subcellular location prediction," Protein Engineering, Vol. 12, no. 2, pp. 107-118, 1999.
57. T. Liu, X. Zheng, and J. Wang, "Prediction of protein structural class using a complexity-based distance measure," Amino Acids, Vol. 38, no. 3, pp. 721-728, 2010.
58. A. Tassanakajon, K. Somboonwiwat, and P. Amparyup, "Sequence diversity and evolution of antimicrobial peptides in invertebrates," Developmental & Comparative Immunology, 2014.
59. J. Wright, A. Y. Yang, A. Ganesh, S. S. Sastry, and Y. Ma, "Robust face recognition via sparse representation," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 31, no. 2, pp. 210-227, 2009.
60. L. Zhang, M. Yang, and X. Feng, "Sparse representation or collaborative representation: which helps face recognition?" in Proceedings of the IEEE International Conference on Computer Vision (ICCV '11), pp. 471-478, November 2011.
61. B. Gan, C.-H. Zheng, J. Zhang, and H.-Q. Wang, "Sparse representation for tumor classification based on feature extraction using latent low-rank representation," BioMed Research International, Vol. 2014, Article ID 420856, 7 pages, 2014.
62. S.-Y. Kim, J. Sim, and J. Lee, "Fuzzy k-nearest neighbor method for protein secondary structure prediction and its parallel implementation," in Computational Intelligence and Bioinformatics, Vol. 4115 of Lecture Notes in Computer Science, pp. 444-453, Springer, Berlin, Germany, 2006.
63. T. Zhang, R. Ji, W. Liu, D. Tao, and G. Hua, "Semi-supervised learning with manifold fitted graphs," in Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI '13), pp. 1896-1902, Beijing, China, August 2013.
64. G. Wang, X. Li, and Z. Wang, "APD2: The updated antimicrobial peptide database and its application in peptide design," Nucleic Acids Research, Vol. 37, supplement 1, pp. D933-D937, 2009.